1. Field of Invention
This invention relates generally to the field of quantitative sedimentologic and stratigraphic prediction, and more specifically, to quantitative prediction of sedimentologic and stratigraphic attributes at all locations within a basin, especially those that are remote from a set of specific data sampling locations. Sedimentologic and stratigraphic prediction is an important step in the discovery and recovery of oil, gas, and water resources.
2. Description of Relevant Art
Sedimentology is the study of rocks that are formed by: (1) the deposition of rock fragments which have been transported from their source to another location by water and/or air (e.g., sandstone and shale); (2) precipitation of minerals from a liquid or solution (e.g., salt, gypsum); and (3) remains (shells, skeletons and organic matter) of organisms (e.g., limestone, coal). Sedimentary rocks are deposited in layers known as strata. Stratigraphy is the study of the origin, composition, distribution and succession of these strata.
Oil and gas reservoirs and groundwater resources occur in sedimentary basins filled with strata of diverse compositions that contain fluids (water, oil, gas) in variable proportions and spatial distributions. The distribution of fluids is strongly controlled by petrophysical (e.g., porosity and permeability) and geometric (e.g., continuity and connectivity) properties of strata.
To recover petroleum from these reservoirs typically requires drilling through thousands of feet of overlying rock. The drilling of oil and gas wells is normally a very expensive endeavor. Consequently, before incurring this expense, those involved in the exploration for or production of oil and gas reservoirs seek to obtain an understanding of the basin geology and, in particular, the basin sedimentology and stratigraphy, so that an oil or gas well is drilled in a location that is most likely to achieve an economic success. In oil and gas exploration, geologic and seismic data are used to predict the location of sedimentary rocks and structures that are likely to contain an oil or gas reservoir. In developing (producing) an oil or gas reservoir, geologic and seismic data are used to predict locations for drilling wells that will facilitate the extraction of more petroleum from the identified reservoir.
In groundwater and contaminant transport modeling, the scientific problems of correctly identifying the fluid-flow pathways are the same as they are for oil and gas exploration and production, even though groundwater typically occurs at much shallower depths. It is widely appreciated that the biggest problem in groundwater and contaminant transport modeling is the definition of subsurface stratigraphy.
Presently, several techniques are used to obtain direct or indirect information about sedimentologic and stratigraphic attributes. A common technique is seismic surveying, which involves: (1) transmitting sound waves from the surface into the earth; (2) recording the waves that are reflected back to the surface when the transmitted wave encounters interfaces between strata, fractures and other discontinuities that reflect acoustic waves in the underlying earth; and (3) analyzing the reflected signals to make geological inferences about sedimentary rocks and fluids encountered by the waves as they propagate through the earth. Seismic methods obtain indirect information (inferences) about rocks and fluids only at the sites of the seismic line. Other common techniques include coring cuttings and well logging, which involve taking samples of the various rocks and fluids encountered as a well is drilled, and inserting various instruments into the well to measure various rock and fluid properties. These techniques obtain direct and indirect information only at the coring or well sites.
Most techniques for obtaining sedimentologic and sedimentary data or inferences about their attributes are relatively expensive. Moreover, the results obtained from such techniques are limited and applicable only to the locations at which the data are taken; i.e., the data obtained by any one of these techniques at a particular location are not necessarily representative or predictive of the stratigraphy as it exists beyond a short radial distance from the precise location at which the data were taken. As a consequence, any conclusions drawn with respect to sedimentological and sedimentary attributes are subject to increasing uncertainty as the location of interest becomes increasingly remote from the locations at which the data are taken. Equally important, the information is indirect, that is, the information generated are no more than geological inferences from proxy measurements. Because of these limitations, a model is needed that accurately predicts stratigraphical attributes within a given basin from a small number of data sets.
In the parent application, Ser. No. 09/239,634, filed on Jan. 29, 1999, applicant disclosed a method that solves such a problem in that it accurately predicts basin stratigraphy at locations remote from where initial geologic data sets are collected. The disclosed method utilizes data collected from a few distinct locations within a desired basin. These data are compared to a predicted set of data generated from a forward stratigraphic model that is fed a set of values for the model process parameters. The predicted and the actual data sets are compared, and if the difference is greater than a predetermined limit, the model is run again with the parameter values modified. This process is repeated until the predictions fall within the predetermined limit and are close to the measurements taken at the sample locations. In the parent application, the predicted data set produced an accurate two-dimensional depiction of the sedimentologic and stratigraphic attributes of the desired basin thus providing a significant advance over other existing modeling techniques. However, the disclosed method of the parent application lacked the capability to generate a three-dimensional model of the sedimentologic and stratigraphic attributes of the desired basin.
Accordingly, this invention is directed to using geological data generated from one or more locations to accurately predict the stratigraphy at a location or locations remote from where the geological data were initially collected to produce a three-dimensional model of the sedimentologic and stratigraphic attributes of the desired basin. In particular, geological data gathered at a specific location can be input into the disclosed process and the stratigraphy for a location as much as tens of kilometers or as close as tens of meters away from the initial data point can be accurately predicted. The ability to predict the stratigraphy is accomplished using a mathematical optimization technique known as inversion.
Quantitative stratigraphic predictions made using inversion techniques reduce risks associated with exploration and production of oil and gas, or definition of fluid-flow pathways in ground water, and enhance interpretations or predictions made from other available data sets. For instance, quantitative prediction of the stratigraphy can be used to: (1) refine what has been inferred about the stratigraphy at a remote location by other techniques; (2) explain what a particular seismic image means in terms of rock type or other stratigraphic property; (3) extend with greater confidence information recovered from a well to a volume of rock a significant distance from the well; or (4) eliminate stratigraphically unreasonable solutions from a population of possible solutions of subsurface geology predicted by other techniques.
In the context of sedimentology and stratigraphy, inversion involves the use of: (1) a forward model to predict stratigraphy throughout a sedimentary basin based upon the values of realistic input parameters; (2) real stratigraphic data from a relatively small number of distinct locations within the sedimentary basin; and (3) an inversion technique that: (a) determines the difference between the measured stratigraphic data and the predictions made by the forward model for the locations at which the real stratigraphic data were obtained; and (b) if the differences are unacceptable, modifies the values of the input parameters to the forward model to achieve a closer match between the predicted stratigraphic attributes and the measured or observed stratigraphic attributes. The process of using the forward model to predict the stratigraphy throughout the basin and the modification of the values of the input parameters continues until the predictions made by the forward model for the locations associated with the real stratigraphic data match or are reasonably close to the real stratigraphic data. At this point, the forward model has been tuned such that it accurately predicts the stratigraphy not just at the locations associated with the real data, but also at other locations within the three-dimensional volume that are remotely situated from the sample locations.
Even though mathematical inversion has been applied in a number of geoscience and geoengineering applications (including seismic signal processing, well logging, potential field geophysics, petrophysics, hydrology, contaminant transport and oil maturation analysis), it had not been applied to stratigraphic analysis or to prediction of rock attributes beyond and/or between points of control until the applicant did so in the parent application. One principal reason that inversion had not been applied to stratigraphic analysis is that it was regarded for a long time as theoretically impossible. Ian Lerche, one of the world""s leaders in applying inverse and other optimization techniques to geoscience and geoengineering problems, co-authored an influential paper in 1987 which concluded that the application of inversion and other optimization techniques to the analysis of sedimentary rocks was theoretically impossible (Burton, et al., 1987).
The conclusion by Burton, et al., that inversion of stratigraphic data was theoretically impossible was based upon their determination that the different processes involved in producing the stratigraphy of a sedimentary basin and the different parameter values (e.g., magnitude, rates) associated with these processes can substitute or compensate for each other to produce the same stratigraphy in the sedimentary basin of interest. If different combinations and values of processes can substitute for each other to produce the same stratigraphy, then it is impossible to uniquely determine the values of the input parameters of the forward model to accurately predict the stratigraphy over a three-dimensional volume. In mathematical terms, this condition is known as nonuniqueness.
In the development of the present invention, it was discovered that the nonuniqueness conclusion reached by Burton, et al., was attributable to two aspects of the forward model that they employed. First, the philosophies incorporated in the forward model reflected stratigraphic paradigms which are now known not to be true, including: (1) the assumption that stratigraphic processes substitute for each other to produce identical products; (2) a belief that the stratigraphic record is dominantly composed of the deposits of rare, haphazard events that lack pattern and which, are therefore, not invertible; (3) that conservation of mass is not a requirement of the stratigraphic process-response system; and (4) that so much opf the rock record is missingxe2x80x94a condition known as stratigraphic gapsxe2x80x94that remaining information is not sufficient to reconstruct the stratigraphic history and the current distribution of different rock types. Second, their forward model used to test whether inversion could be applied to stratigraphy was a strictly geometric model, and did not simulate the process-response system of the real world adequately nor simulate stratigraphic properties such as facies successions and cycles which has been found to contain robust information.
The disclosed invention employs a forward model that models the processes associated with creating the stratigraphy in a sedimentary basin. In this regard, conservation of mass is identified as being a key component of the stratigraphic process-response system emulated by the forward model. Another is simulating stratigraphic, sedimentologic and biologic processes in the energy domain (i.e., potential, kinetic, chemical and biologic energy). Further, the types of geological data that have a significant impact on comparing forward model predictions with observations, i.e., robust types of data, have been identified and incorporated into the forward model.
Among the mathematical inversion techniques that are suitable for use in the disclosed invention are the genetic, the simulated annealing, the Monte Carlo, the gradient descent, and the technique designed by Ian Lerche. Since the inversion technique typically requires a number of forward model iterations (repeatedly running the forward model and modifying the input parameters) before the forward model produces an accurate prediction of the stratigraphy, the speed at which the forward model system operates may be of concern in some applications. Presently, the Lerche and the simulated annealing inversion techniques are found to be the fastest and best suited optimization techniques for this application.
Aside from predicting stratigraphy for oil and gas operations, the disclosed invention is equally applicable to groundwater hydrology and contaminant transport modeling as will be appreciated by those persons skilled in the art. Additionally, persons skilled in the art will recognize that stratigraphic inversion provides a quantitative link among geoscience and geoengineering disciplines. Som of these allied disciplines routinely apply inverse methods predict rock or fluid attributes from observations and models appropriate to their disciplines. None of these allied disciplines, however, has used a stratigraphic forward model in the inversion. For example, hydrology uses Darcy flow forward models, seismic geophysics uses some form of the wave equation as its forward model, and well bore geophysics uses a petrophysical forward model. The result of inversions of each disciplinary model is a population of solutions that presumably contain the correct solution. Each of these disciplines is attempting to identify a correct stratigraphy or fluid distribution based upon knowledge, models and data from one data type.
Thus this invention also discloses the performance of simultaneous inversions on multiple data types from two or more disciplines. Without a quantitative method of predicting stratigraphy, those persons skilled in the art of other geoscience or geoengineering disciplines have not been able to link these disciplines and perform simultaneous inversions on multiple data types. As an example, inversions on fluid data (e.g., pressure, head, composition, gas/oil ratio, historical production and pressure decline) using a Darcy forward model produces a population of models that describe likely fluid-flow (gas, oil or water) pathways through strata, independent of any stratigraphical information. Some of these solutions are geologically possible; others are geologically unrealistic. Similarly, stratigraphic inversion on the same strata, independent of information about fluid distribution and flow pathways, produces a population of solutions of which some are unrealistic with respect to fluid distribution. By simultaneously inverting on both fluid and rock data types, a smaller population of solutions is calculated and unrealistic solutions are eliminated. Since inversions on one data type eliminate a portion of possible solutions calculated by inversions on a different data type, the number of possible solutions and uncertainty are reduced, and accuracy is enhanced.